The present invention relates generally to digital imaging, and more particularly to reconstructing a three dimensional (3D) image using a tomosynthesis device.
It is well know in the medical community that breast cancer is a leading cause of death in women (and to a lesser extent also affects men). When early detection of abnormalities is combined with proper medical attention, however, the risk of death and/or severe medical ramifications can be drastically reduced. Many devices and techniques (e.g., mammography) are currently under development to detect breast abnormalities earlier, and with greater accuracy than conventional devices. A brief summary of some conventional devices, techniques, and their limitations follows.
Presently, the vast majority of mammography devices utilize conventional x-ray techniques. A patient""s breast is positioned in an x-ray machine, which passes x-rays through the breast and generates a corresponding x-ray image on a film. The film is then analyzed by a trained clinician, who examines the film for abnormalities, such as a mass, a cyst, a microcalcification, a fibrous finding, an architectural distortion, and/or other abnormal findings related with benign or malignant abnormalities. In standard digital mammography, the x-ray image (or projection radiograph) is acquired by means of a digital detector, and the resulting digital image can be processed to enhance the visibility of structures within the image, thus providing a potentially more useful image to the clinician. These standard mammography techniques, however, suffer from many problems.
The 2D nature of standard mammography techniques (including standard digital and film based) can lead to superposition (e.g., overlay) problems. Superposition can occur when multiple structures are overlaid onto the same position in the projection image. The overlaid normal (i.e., non-malignant) structures may end up combining in appearance to appear as an abnormality, resulting in a xe2x80x9cfalse positivexe2x80x9d identification of an abnormality. Presently, the false positive rate is relatively high: on the order of between 70% and 90% of biopsies are normal. Conversely, real abnormalities may be superimposed over dense tissue regions which xe2x80x9chidexe2x80x9d the abnormality within the dense tissue, resulting in a xe2x80x9cfalse negativexe2x80x9d miss of an abnormality. Thus, in standard 2D imaging (e.g., projection radiography) structures within the breast may become superimposed with each other, thereby normal structures within the breast can xe2x80x9cinterferexe2x80x9d with a clear interpretation of structures of interest (e.g., potentially malignant) which are located at a different height (relative to the projection direction) within the imaged object.
Another problem with many mammography techniques is related to contrast issues. A small structure within the breast appears with a relatively low contrast in the projection image, when compared to its true 3D contrast. For example, in a projection image of a breast with a thickness of 6 cm, a structure with a 2 cm thickness appears with only a third of its true contrast; a structure with 1 cm thickness appears with only a sixth of its true contrast, etc. Thus, the contrast in the image does not correctly represent the true contrast of the structure.
To improve on the limitations of 2D techniques, some techniques utilize a plurality of projection radiographs of a patient""s breast to create a 3D image of the breast tissue. The 3D image is then examined by a trained clinician for indications of breast abnormalities. In these 3D techniques, the breast to be imaged is radiated from different projection angles. The radiation passing through the breast is used to generate a plurality of projection radiographs or xe2x80x9c2D viewsxe2x80x9d of the breast. A three dimensional (3D) image of the breast is then generated from the views using conventional or newly developed algorithms. Generally, the reconstructed 3D image is organized as a set of 2D images, or xe2x80x9cslicesxe2x80x9d, which are substantially parallel to the detector plane. As used herein, an xe2x80x9cimage slicexe2x80x9d is a single image representative of the structures within an imaged object (e.g., breast tissue) at a fixed height above the detector. Other arrangements of the data representing the 3D image of the object are also possible, as would be readily apparent to one of ordinary skill in the art after reading this disclosure. One technique of generating a 3D image from a plurality of radiographs is known as simple backprojection. Conventional 3D image reconstruction techniques (such as those involving simple backprojection), however, also suffer from disadvantages.
In particular, high contrast structures in the imaged object can lead to severe artifacts that cause a significant reduction in the quality and the diagnostic value of reconstructed images. These artifacts are due to the fact that generally, image information due to structures in the imaged object not only contribute to the reconstruction at the corresponding true location of the structure within the reconstructed 3D image, but at other locations as well. The corresponding artifacts are known as out-of-plane artifacts, or streak artifacts. Conventional 3D reconstruction techniques, however, do not adequately remove or reduce artifacts.
In digital tomosynthesis, for example, one backprojection technique known as xe2x80x9csimple backprojectionxe2x80x9d or the xe2x80x9cshift and add algorithmxe2x80x9d is often used to reconstruct images (e.g., 3D images) due to its relatively straightforward implementation and minimal computational power requirements. The shift and add algorithm, however, introduces reconstruction artifacts. In fact, high contrast out-of-plane structures tend to appear as several relatively low-contrast copies in a reconstructed horizontal slice through the object. Also, the previously described loss in contrast for small structures is not recovered by the simple backprojection reconstruction technique. Thus, the conventional shift and add algorithm suffers from considerable problems in this field of use.
Another reconstruction method used in tomosynthesis is known as the algebraic reconstruction technique (ART). ART tends to generate higher quality reconstructions than the shift and add algorithm, but is typically much more computational heavy than other techniques (e.g., the shift and add algorithm). This computational cost and the associated delay until the final 3D image of the breast is available to the clinician, can be prohibitive in practical clinical use.
Another reconstruction technique used in computed tomography (CT) imaging (i.e., filtered back-projection) utilizes projections over the full angular range (i.e., full 360xc2x0 image acquisition about the object to be imaged) and a fine angular spacing between projections. Within this framework, filtered backprojection is a reconstruction method that yield high quality reconstructions with few artifacts. Unfortunately, full 360xc2x0 image acquisition is not practical for many applications including breast imaging, where design considerations limit the ability to rotate fully about the breast.
Thus, a need exists for a method and apparatus for reconstructing a three dimensional (3D) image of an object (or other, but different reconstructed 2D images, for example cross-sectional images) from a plurality of two dimensional (2D) views.
The present invention is directed at reducing or eliminating one or more of the problems set forth above, and other problems found within the prior art.
According to one aspect of the present invention, a method of constructing a three dimensional (3D) image of an object from a plurality of two dimensional (2D) views of the object is provided comprising the steps of filtering the plurality of 2D views of the object, and order statistics-based backprojecting the filtered 2D views into the 3D image of the object.
According to another aspect of the present invention, a program product is provided for causing a tomosynthesis device to perform the steps of acquiring a plurality of 2D views of an object to be imaged, filtering the acquired 2D views, and order statistics-based backprojecting the filtered 2D views into a 3D image of the object.
According to another aspect of the present invention, a method of compensating a 2D view for the thickness of an object to be analyzed, the view including pixels corresponding to rays passing through the object and pixels corresponding to rays not passing through the object is provided comprising the steps of determining a boundary curve, the boundary curve being the curve separating the pixels corresponding to rays passing through the object from the pixels corresponding to rays not passing through the object, calculating a distance from each pixel corresponding to rays passing through the object to the boundary curve, calculating an average pixel image value versus the distance from the boundary curve, and offsetting the image values at pixels corresponding to rays passing through the object such that the average pixel image value versus the distance from the boundary curve is about constant.
According to another aspect of the present invention an imaging device for constructing a three dimensional (3D) image of an object from a plurality of two dimensional (2D) views of the object is provided comprising a radiation source for emitting radiation through the object to be imaged, the radiation source being positionable at an angle of projection wherein each of the plurality of 2D views corresponds to a given position of the radiation source, a detector positioned to detect radiation passing through the object to be imaged, the detector generating a signal representing a view of the object, and a processor electrically coupled to the detector for analyzing the signal. The processor is programmed to perform the steps of filtering the plurality of 2D views, and order statistics-based backprojecting the filtered 2D views into the 3D image of the object.
According to another aspect of the present invention, a method of reconstruction of three dimensional (3D) structures from a plurality of projection radiographs of tissue taken at different angles, the method is provided comprising the steps of digitally acquiring a plurality of projection radiographs taken at different angles, segmenting each of the digitally acquired projection radiographs into pixels corresponding to rays passing through the tissue and pixels corresponding to rays not passing through the tissue, compensating the image values at segmented pixels for a thickness of the tissue, filtering the compensated pixels to enhance structures depicted in the projection radiographs, and order statistics-based backprojecting the filtered images into a reconstructed 3D representation of the tissue.
According to another aspect of the present invention, a method of constructing a three dimensional (3D) image of an object from a plurality of two dimensional (2D) views of the object is provided comprising the steps of 2D filtering the plurality of 2D views of the object, and simple backprojecting the filtered 2D views into the 3D image of the object.